The parameter values used in a tire model directly determine the prediction accuracy of the model. Poorly identified parameters lead to incorrect prediction of tire performances. The optimization algorithm used for parameter identification has a huge impact on the quality of the identified parameters for a tire model. In this paper, four different optimization algorithms in MATLAB, including local optimization algorithms (fminsearchcon and patternsearch) and global optimization algorithms (particleswarm and GA-genetic algorithm), are applied to identify the parameters of a newly proposed in-plane flexible ring tire model based on one cleat experiment results, respectively. Their performances are compared in terms of the prediction accuracy, efficiency and some other aspects. After the comparison, the most suitable optimization algorithm for tire model parameter identification is obtained. Finally, the parameters that are identified based on the set of parameters from the most suitable algorithm are used to predict the other cleat test conditions to further validate the tire model.